Troels Wesenberg Kjaer

Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome.

Electroencephalography (EEG) for neurological prognostication after cardiac arrest and targeted temperature management; rationale and study design

BackgroundElectroencephalography (EEG) is widely used to assess neurological prognosis in patients who are comatose after cardiac arrest, but its value is limited by varying definitions of pathological patterns and by inter-rater variability. The American Clinical Neurophysiology Society (ACNS) has recently proposed a standardized EEG-terminology for critical care to address these limitations.In the Target Temperature Management (TTM) trial, a large international trial on temperature management after cardiac arrest, EEG-examinations were part of the prospective study design. The main objective of this study is to evaluate EEG-data from the TTM-trial and to identify malignant EEG-patterns reliably predicting a poor neurological outcome.Methods/DesignIn the TTM-trial, 399 post cardiac arrest patients who remained comatose after rewarming underwent a routine EEG. The presence of clinical seizures, use of sedatives and antiepileptic drugs during the EEG-registration were prospectively documented.After the end of the trial, the EEGs were retrieved to form a central EEG-database.The EEG-data will be analysed using the ACNS EEG terminology. We designed an electronic case record form (eCRF). Four EEG-specialists from different countries, blinded to patient outcome, will independently classify the EEGs and report through the eCRF. We will describe the prognostic values of pre-specified EEG patterns to predict poor as well as good outcome. We hypothesise three patterns to always be associated with a poor outcome (suppressed background without discharges, suppressed background with continuous periodic discharges and burst-suppression). Inter- and intra-rater variability and whether sedation or level of temperature affects the prognostic values will also be analyzed.DiscussionA well-defined terminology for interpreting post cardiac arrest EEGs is critical for the use of EEG as a prognostic tool.The results of this study may help to validate the ACNS terminology for assessing post cardiac arrest EEGs and identify patterns that could reliably predict outcome.Trial registrationThe TTM-trial is registered at ClinicalTrials.gov (NCT01020916).

SSVEP-modulation by covert and overt attention: Novel features for BCI in attention neuro-rehabilitation.

In this pilot study the effect of attention (covert and overt) on the signal detection and classification of steady-state visual-evoked potential (SSVEP) were investigated. Using the SSVEP-based paradigm, data were acquired from 4 subjects using 3 scalp electroencephalography (EEG) electrodes located on the visual area. Subjects were instructed to perform the attention task in which they attended covertly or overtly to either of the stimuli flickering with different frequencies (6, 7, 8 and 9Hz). We observed a decrease in signal power in covert compared to the overt attention. However, there was a consistent pattern in covert attention causing an increase in the power of the 2nd harmonic of the attended frequency. Encouraging results of this preliminary study indicates that it can be adapted and implemented in the brain-computer interface (BCI) system which could potentially be used as a neuro-rehabilitation tool for individuals with attention deficit.

Cerebrospinal fluid levels of catecholamines and its metabolites in Parkinson's disease: Effect of L‐DOPA treatment and changes in levodopa‐induced dyskinesia

Levodopa (l‐DOPA, l‐3,4‐dihydroxyphenylalanine) is the most effective drug in the symptomatic treatment of Parkinsons disease (PD), but chronic use initiates a maladaptive process leading to l‐DOPA‐induced dyskinesia (LID). Risk factors for early onset LID include younger age, more severe disease at baseline and higher daily l‐DOPA dose, but biomarkers to predict the risk of motor complications are not yet available. Here, we investigated whether CSF levels of catecholamines and its metabolites are altered in PD patients with LID [PD‐LID, n = 8)] as compared to non‐dyskinetic PD patients receiving l‐DOPA (PD‐L, n = 6), or not receiving l‐DOPA (PD‐N, n = 7) as well as non‐PD controls (n = 16). PD patients were clinically assessed using the Unified Parkinsons Disease Rating Scale and Unified Dyskinesia Rating Scale and CSF was collected after overnight fasting and 1–2 h after oral intake of l‐DOPA or other anti‐Parkinson medication. CSF catecholamines and its metabolites were analyzed by HPLC with electrochemical detection. We observed (i) decreased levels of dihydroxyphenylacetic acid (DOPAC) and homovanillic acid in PD patients not receiving l‐DOPA (ii) higher dopamine (DA) levels in PD‐LID as compared to controls (iii) higher DA/l‐DOPA and lower DOPAC/DA ratios in PD‐LID as compared to PD‐L and (iv) an age‐dependent increase of DA and decrease of DOPAC/DA ratio in controls. These results suggest increased DA release from non‐DA cells and deficient DA re‐uptake in PD‐LID. Monitoring DA and DOPAC in CSF of l‐DOPA‐treated PD patients may help identify patients at risk of developing LID.

A brain computer interface for robust wheelchair control application based on pseudorandom code modulated Visual Evoked Potential

In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO® MINDSTORM® EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application.

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy – A comparison with scalp EEG monitoring

OBJECTIVE Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit. METHODS We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes. RESULTS There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. CONCLUSIONS Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. SIGNIFICANCE Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis.

Drug taper during long‐term video‐EEG monitoring: efficiency and safety

Anti‐epileptic drugs (AED) are often tapered to reduce the time needed to record a sufficient number of seizure during long‐term video‐EEG monitoring (LTM). Fast AED reduction is considered less safe, but few studies have examined this. Our goal is to examine whether the rate of AED reduction affects efficiency and safety.

Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla

Purpose Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. Materials and methods The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18–70 years) and 13 patients with epilepsy (8 males, age range 21–67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). Results RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality. Conclusion This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI.

Hypoglycemia-Associated EEG Changes Following Antecedent Hypoglycemia in Type 1 Diabetes Mellitus

BACKGROUND Recurrent hypoglycemia has been shown to blunt hypoglycemia symptom scores and counterregulatory hormonal responses during subsequent hypoglycemia. We therefore studied whether hypoglycemia-associated electroencephalogram (EEG) changes are affected by an antecedent episode of hypoglycemia. METHODS Twenty-four patients with type 1 diabetes mellitus (10 with normal hypoglycemia awareness, 14 with hypoglycemia unawareness) were studied on 2 consecutive days by hyperinsulinemic glucose clamp at hypoglycemia (2.0-2.5 mmol/L) during a 1-h period. EEG was recorded, cognitive function assessed, and hypoglycemia symptom scores and counterregulatory hormonal responses were obtained. RESULTS Twenty-one patients completed the study. Hypoglycemia-associated EEG changes were identified on both days with no differences in power or frequency distribution in the theta, alpha, or the combined theta-alpha band during hypoglycemia on the 2 days. Similar degree of cognitive dysfunction was also present during hypoglycemia on both days. When comparing the aware and unaware group, there were no differences in the hypoglycemia-associated EEG changes. There were very subtle differences in cognitive function between the two groups on day 2. The symptom response was higher in the aware group on both days, while only subtle differences were seen in the counterregulatory hormonal response. CONCLUSION Antecedent hypoglycemia does not affect hypoglycemia-associated EEG changes in patients with type 1 diabetes mellitus.

Time-Dependent Decline in Multifocal Electroretinogram Requires Faster Recording Procedures in Anesthetized Pigs

Purpose The time-dependent effect of anesthetics on the retinal function is debated. We hypothesize that in anesthetized animals there is a time-dependent decline that requires optimized multifocal electroretinogram (mfERG) recording procedures. Methods Conventional and four-frame global-flash mfERG recordings were obtained approximately 15, 60, and 150 minutes after the induction of propofol anesthesia (20 pigs) and isoflurane anesthesia (nine pigs). In six of the propofol-anesthetized pigs, the mfERG recordings were split in 3-minute segments. Two to 4 weeks after initial recordings, an intraocular injection of tetrodotoxin (TTX) was given and the mfERG was rerecorded as described above. Data were analyzed using mixed models in SAS statistical software. Results Propofol significantly decreases the conventional and global-flash amplitudes over time. The only significant effect of isoflurane is a decrease in the global-flash amplitudes. At 15 minutes after TTX injection several of the mfERG amplitudes are significantly decreased. There is a linear correlation between the conventional P1 and the global-flash DR mfERG-amplitude (R2 = 0.82, slope = 0.72, P < 0.0001). There is no significant difference between the 3-minute and the prolonged mfERG recordings for conventional amplitudes and the global-flash direct response. The global flash–induced component significantly decreases with prolonged mfERG recordings. Conclusions A 3-minute mfERG recording and a single stimulation protocol is sufficient in anesthetized pigs. Recordings should be obtained immediately after the induction of anesthesia. The effect of TTX is significant 15 minutes after injection, but is contaminated by the effect of anesthesia 90 minutes after injection. Therefore, the quality of mfERG recordings can be further improved by determining the necessary time-of-delay from intraocular injection of a drug to full effect. Translational Relevance General anesthesia is a possible source of error in mfERG recordings. Therefore, it is important to investigate the translational relevance of the results to mfERG recordings in children in general anesthesia.